Full Stack Java Engineer_AI
Goldenpick Technologies
Weehawken, NJ, United States
about 1 month ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Artificial Intelligence
Microsoft Azure
Code Review
Continuous Integration
Software Debugging
Distributed Systems
IBM WebSphere MQ
Enterprise Messaging Systems
Systems Development Life Cycle
Release Management
Software Engineering
+11 more
Systems Integration
Workflow Management Systems
Enterprise Software Applications
Prompt Engineering
Spring-boot
Enterprise Integration
Apache Kafka
Virtual Agents
Api Design
Restful APIs
Serverless Computing
Job description
- Design and develop REST APIs, event-driven integrations, and messaging interfaces.
- Build and maintain integrations between Loan IQ and enterprise applications.
- Design and implement AI-powered agents and workflows that improve SDLC processes and engineering productivity.
- Leverage AI-assisted development tools to accelerate coding, testing, debugging, code reviews, and documentation.
- Collaborate with QA, Business Analysts, Product Owners, and Architects to deliver end-to-end solutions.
- Conduct code reviews and promote engineering, integration, and cloud best practices.
- Contribute to CI/CD automation, release management, and deployment processes.
- Design and implement cloud-native integration solutions using Azure services and serverless technologies.
- Troubleshoot production issues and optimize application and integration performance.
Requirements
- Core Engineering
- 8+ years of software engineering experience, ideally within Financial Services.
- Strong expertise in Java, Spring Boot, REST APIs, and distributed systems.
- Experience with Kafka, IBM MQ, or similar messaging technologies.
- Strong integration experience with Loan IQ, lending, banking, or enterprise platforms.
- Deep understanding of API design, system integration, and enterprise application architecture.
- Agentic AI & Software Engineering
- Experience building AI Agents and Agentic Software Engineering solutions to automate and enhance SDLC processes.
- Hands-on experience with Java-based AI frameworks such as Spring AI, LangChain4j, Semantic Kernel, MCP (Model Context Protocol), or similar technologies.
- Experience implementing RAG, prompt engineering, tool calling, workflow orchestration, and agent-based architectures.
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